LegalWorld is a life-cycle interactive environment modeling Chinese civil litigation as five causally connected stages grounded in 75,309 judgments, paired with LongJud-Bench for cross-stage agent evaluation.
Two Tales of Persona in LLMs:
10 Pith papers cite this work. Polarity classification is still indexing.
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ZIPP conditions diffusion models on LLM-rewritten prompts derived from graph-mined natural-language personas to achieve zero-shot personalization, reporting 13-20% gains and 79% human preference win rate over generic outputs.
Psy-CoT decomposes reasoning into Interaction Perception, Psychological Empathy, and Logical Construction while RAPO asymmetrically weights role-specific tokens during policy optimization, outperforming prior CoT and GRPO baselines on role-playing benchmarks.
REVERIEMEM is a three-layer perspective-bounded memory system that raises knowledge boundary fidelity by 34.6 points and wins ~79% of narrative comparisons on a new book-based role-playing benchmark.
IVIE generates complete playable interactive fiction worlds via a four-stage incremental pipeline that combines LLM creativity with symbolic validation for coherence.
GenPT applies generative projective testing to LLM agents and reports lower directional bias plus greater longitudinal sensitivity than self-report questionnaires.
Profile-conditioned LLMs achieve higher tacit alignment with humans on subjective spectra when traits match, as quantified by the new Tacit Understanding Index (TUX) from 241 humans and 200 agents.
An extended annotation scheme with new categories and attributes plus a Gemma-300M-based multi-head classifier achieves 81.6% macro F1 on personal fact classification, outperforming few-shot LLM baselines by nearly 9 points with lower compute.
TSUBASA improves long-horizon personalization in LLMs via dynamic memory evolution for writing and context-distillation self-learning for reading, outperforming Mem0 and Memory-R1 on Qwen-3 benchmarks while reducing token use.
Synthia creates scalable personas from Bluesky posts that better match human survey responses than prior methods, uses smaller models, and retains social network structure for network-aware analysis.
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